All the base networks employed in this study are pre-trained on the ImageNet dataset [1]}. The inputs to the ensemble systems are obtained by forward passing the datasets through the fine-tuned networks and extracting the features of the last pooling layer (2048 neurons).
Note that for a fair comparison, no extra randomness such as data augmentation, has been applied during training or feature extraction.
